{"total":34,"rows":[{"id":"2204.12993","title":"Counterfactual harm","created":"2022-04-27","cited_by_count":29,"area":null},{"id":"2108.13025","title":"Transport-based Counterfactual Models","created":"2021-08-30","cited_by_count":27,"area":null},{"id":"2202.10806","title":"Stochastic Causal Programming for Bounding Treatment Effects","created":"2022-02-22","cited_by_count":25,"area":null},{"id":"2311.16026","title":"A Neural Framework for Generalized Causal Sensitivity Analysis","created":"2023-11-27","cited_by_count":17,"area":null},{"id":"2202.13774","title":"Selection, Ignorability and Challenges With Causal Fairness","created":"2022-02-28","cited_by_count":16,"area":null},{"id":"2208.03843","title":"Counterfactual Fairness Is Basically Demographic Parity","created":"2022-08-07","cited_by_count":15,"area":null},{"id":"2306.01424","title":"Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model","created":"2023-06-02","cited_by_count":14,"area":null},{"id":"2106.07057","title":"FairCanary: Rapid Continuous Explainable Fairness","created":"2021-06-13","cited_by_count":12,"area":null},{"id":"2201.05893","title":"Treatment Effect Risk: Bounds and Inference","created":"2022-01-15","cited_by_count":12,"area":null},{"id":"2210.05446","title":"Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders","created":"2022-10-11","cited_by_count":10,"area":null},{"id":"2311.18460","title":"Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework","created":"2023-11-30","cited_by_count":10,"area":null},{"id":"2311.12447","title":"Designing Long-term Group Fair Policies in Dynamical Systems","created":"2023-11-21","cited_by_count":9,"area":null},{"id":"2302.11944","title":"Counterfactual Situation Testing: Uncovering Discrimination under Fairness given the Difference","created":"2023-02-23","cited_by_count":8,"area":null},{"id":"2410.09600","title":"The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning","created":"2024-10-12","cited_by_count":8,"area":null},{"id":"2210.15901","title":"Mitigating Health Disparities in EHR via Deconfounder","created":"2022-10-28","cited_by_count":7,"area":null},{"id":"2305.01397","title":"Are demographically invariant models and representations in medical imaging fair?","created":"2023-05-02","cited_by_count":6,"area":null},{"id":"2212.07877","title":"Manifestations of Xenophobia in AI Systems","created":"2022-12-15","cited_by_count":4,"area":null},{"id":"2202.03792","title":"Counterfactual Multi-Token Fairness in Text Classification","created":"2022-02-08","cited_by_count":3,"area":null},{"id":"2205.01072","title":"The Equity Framework: Fairness Beyond Equalized Predictive Outcomes","created":"2022-04-18","cited_by_count":2,"area":null},{"id":"2210.12368","title":"Counterfactual Generation Under Confounding","created":"2022-10-22","cited_by_count":2,"area":null},{"id":"2401.13408","title":"Toward A Causal Framework for Modeling Perception","created":"2024-01-24","cited_by_count":2,"area":null},{"id":"2502.01267","title":"Counterfactual Situation Testing: From Single to Multidimensional Discrimination","created":"2025-02-03","cited_by_count":2,"area":null},{"id":"2305.18183","title":"On Counterfactual Data Augmentation Under Confounding","created":"2023-05-29","cited_by_count":1,"area":null},{"id":"2410.22382","title":"Debiasing Alternative Data for Credit Underwriting Using Causal Inference","created":"2024-10-29","cited_by_count":1,"area":null},{"id":"2601.03203","title":"Counterfactual Fairness with Graph Uncertainty","created":"2026-01-06","cited_by_count":1,"area":null},{"id":"2602.03459","title":"Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework","created":"2026-02-03","cited_by_count":1,"area":null},{"id":"2112.02170","title":"Counterfactual Fairness in Mortgage Lending via Matching and Randomization","created":"2021-12-03","cited_by_count":0,"area":null},{"id":"2309.01780","title":"Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments","created":"2023-09-04","cited_by_count":0,"area":null},{"id":"2410.17433","title":"Revisiting Technical Bias Mitigation Strategies","created":"2024-10-22","cited_by_count":0,"area":null},{"id":"2502.10161","title":"Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses","created":"2025-02-14","cited_by_count":0,"area":null},{"id":"2601.10089","title":"Bayesian Meta-Analyses Could Be More: A Case Study in Trial of Labor After a Cesarean-section Outcomes and Complications","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2608.03917","title":"Implementing Causal Perception: Competing SCMs and Situated Fairness","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2609.01040","title":"Causal Evidentiary Governance for High-Risk Machine Learning Systems","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.32004","title":"Is invariance all you need for algorithmic fairness? Removing demographic information can create new bias","created":"2026-09-25","cited_by_count":0,"area":null}],"next_cursor":null}